While the predictability of excess stock returns is detected by traditional predictive regressions as statistically small, the direction-of-change and volatility of returns exhibit a substantially larger degree of dependence over time. We capitalize on this observation and decompose the returns...

This paper presents copula functions as a method to derive bivariate distributions. Copula functions allow for the construction of previously unknown bivariate distributions based on known marginals. This paper uses Weibull marginals to construct six bivariate Weibull distributions suitable for...

Gaussian Copula as a model for default correlation has been recently criticized for a number of fallacies in its application to pricing and risk management of financial liabilities. Here we point out an element of model risk that appears to be overlooked. When the Gaussian Copula is applied to...

Copulas are full measures of dependence among random variables. They are increasingly popular among academics and practitioners in financial econometrics for modeling comovements between markets, risk factors, and other relevant variables. A copula's hidden dependence structure that couples a...

In this paper we address the issue of modeling extreme asset co-movements and their implications for the hedging demands of a dynamic portfolio. We propose a model that is able to accommodate an extremal dependence structure through the stationary distribution of the state variables underlying...

Article deals with modelling of mutual dependencies among financial assets. Its aim is to investigate the impacts of different copula assumptions on optimal portfolios, when CVaR optimization is used. Strategic asset allocation perspective is supposed. It is demonstrated that copula functions...

Kernel-based Copula Processes (KCPs), a new versatile tool for analyzing multiple time-series, are proposed here as a unifying framework to model the interdependency across multiple time-series and the long-range dependency within an individual time-series. KCPs build on the celebrated theory of...

An elliptical copula model is a distribution function whose copula is that of an elliptical distribution. The tail dependence function in such a bivariate model has a parametric representation with two parameters: a tail parameter and a correlation parameter. The correlation parameter can be...